The brain dysfunctions underlying schizophrenia are poorly understood. Nevertheless, it is likely that a critical aspect of this disease is a breakdown of the normal information processing functions of the neuronal assemblies. This project would study the activity of neuronal populations in sensory neocortex and investigate how neuronal assembly activity is disrupted in the dissociative anesthetic (PCP) model of schizophrenia. Experimental investigation of this question will require recording large numbers of cells in functioning neural circuits. However, obtaining this data is only the beginning: the computational and statistical machinery to draw meaningful conclusions from such data must also be developed. Here we propose a collaborative research project between a mathematician (Kenneth Harris) and an electrophysiologist (Gyorgy Buzsaki), with the aim of recording, analyzing, and modeling the activity of large neuronal populations in primary sensory cortex and its disruption by psychotomimetic drugs. The project will rely on two techniques we have developed over the last years: large-scale neuronal recordings using silicon microelectrodes; and the data analysis method of peer prediction. The use of silicon probes will allow for estimation of the location of recorded cells, identification of monosynaptic connections between cell pairs, and characterization of neurons as pyramidal cells or interneurons. Experimentally identified assembly structure will be interpreted in the context of this circuit-level information. We will investigate the hypothesis that psychotomimetic effects of low doses of dissociative anesthetics are caused by a partial distortion in assembly organization, whereas larger doses cause a more complete distortion resulting anesthesia. If reliable signatures of psychotomimetic doses on assembly structure are found, this will suggest a novel method of drug screening for antipsychotics, whereby candidate drugs are evaluated by their ability to reverse these signatures.